Medical devices for mapping cardiac tissue

ABSTRACT

Medical devices and methods for making and using medical devices are disclosed. A method for removing an artifact of a biological reference signal present in a biological source signal may comprise sensing a biological reference signal with one or more electrodes and sensing a biological source signal, wherein the biological source signal comprises an artifact of the biological reference signal. The method may further comprise determining, based on the biological reference signal, the artifact of the biological reference signal and subtracting the artifact of the biological reference signal from the sensed biological source signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.14/717,684, filed May 20, 2015, which claims priority under 35 U.S.C.§119 to U.S. Provisional Application Ser. No. 62/007,310, filed Jun. 3,2014, the entirety of which is incorporated herein by reference.

TECHNICAL FIELD

The present disclosure pertains to medical devices and systems. Moreparticularly, the present disclosure pertains to medical devices andmethods for mapping and/or ablating cardiac tissue.

BACKGROUND

A wide variety of intracorporeal medical devices have been developed formedical use, for example, intravascular use. Some of these devicesinclude guidewires, catheters, and the like. These devices aremanufactured by any one of a variety of different manufacturing methodsand may be used according to any one of a variety of methods. Of theknown medical devices and methods, each has certain advantages anddisadvantages. There is an ongoing need to provide alternative medicaldevices as well as alternative methods for manufacturing and usingmedical devices.

BRIEF SUMMARY

This disclosure describes medical devices, systems, and methods formapping and/or ablating cardiac tissue. In a first example, a cathetersystem for mapping a chamber of a heart, the system comprising: a firstplurality of electrodes configured to sense a biological referencesignal; a second plurality of electrodes configured to sense abiological source signal, wherein the biological source signal comprisesan artifact of the biological reference signal; a processor connected tothe second plurality of electrodes, wherein the processor is configuredto: determine, based on the biological reference signal, the artifact ofthe biological reference signal; and subtract the artifact of thebiological reference signal from the sensed biological source signal.

Alternatively or additionally to the examples above, in another example,to determine, based on the biological reference signal, the artifact ofthe biological reference signal, the processor is configured tocompensate for differences between the biological reference signal andthe artifact of the biological reference signal.

Alternatively or additionally to the examples above, in another example,to compensate for differences between the biological reference signaland the artifact of the biological reference signal, the processor isconfigured to generate one or more shifted copies of the biologicalreference signal.

Alternatively or additionally to the examples above, in another example,to compensate for differences between the biological reference signaland the artifact of the biological reference signal, the processor isfurther configured to: generate, based at least in part on the generatedone or more shifted copies of the biological reference signal, anestimated artifact of the biological reference signal.

Alternatively or additionally to the examples above, in another example,to subtract the artifact of the biological reference signal from thesensed biological source signal, the processor is configured to subtractthe estimated artifact of the biological reference signal from thesensed biological source signal.

Alternatively or additionally to the examples above, in another example,to generate, based at least in part on the generated one or more shiftedcopies of the biological reference signal, an estimated artifact of thebiological reference signal, the processor is configured to: form aprojection matrix comprising the biological reference signal and one ormore shifted copies of the biological reference signal; determining aset of linear combination coefficients using a projection technique; andform the estimated artifact of the biological reference signal from theprojection matrix and the set of linear combination coefficients.

Alternatively or additionally to the examples above, in another example,the projection technique comprises of or more of: least-squaresregression; constrained least-squares; maximum likelihood estimation;non-linear programming; and linear programming.

Alternatively or additionally to the examples above, in another example,to generate, based at least in part on the generated one or more shiftedcopies of the biological reference signal, an estimated artifact of thebiological reference signal, the processor is configured to: generate aconvolution matrix H comprising the biological reference signal and oneor more shifted copies of the biological reference signal; and determinean optimal multiplication vector x, such that a product of theconvolution matrix H and the optimal multiplication vector x produce asolution vector b′, where the solution vector b′ is a solution that ismost closely correlated to the biological source signal.

Alternatively or additionally to the examples above, in another example,the processor is further configured to reduce redundancy in thebiological reference signal.

Alternatively or additionally to the examples above, in another example,the processor is further configured to identify beat timings in thebiological reference signal.

Alternatively or additionally to the examples above, in another example,the processor is further configured to: identify beat windows around theidentified beat timings in the biological reference signal and thebiological source signal; and concatenate the beat windows to produce aconcatenated biological reference signal and a concatenated biologicalsource signal.

Alternatively or additionally to the examples above, in another example,the biological reference signal is a far-field signal and the biologicalsource signal is a near-field signal.

Alternatively or additionally to the examples above, in another example,the biological reference signal is a ventricular cardiac signal and thebiological source signal is an atrial cardiac signal.

Alternatively or additionally to the examples above, in another example,the first plurality of electrodes comprise surface electrodes.

In another example, a method for removing an artifact of a biologicalreference signal present in a biological source signal comprises:sensing a biological reference signal with one or more electrodes;sensing a biological source signal, wherein the biological source signalcomprises an artifact of the biological reference signal; determining,based on the biological reference signal, the artifact of the biologicalreference signal; and subtracting the artifact of the biologicalreference signal from the sensed biological source signal.

Alternatively or additionally to the examples above, in another example,determining, based on the biological reference signal, the artifact ofthe biological reference signal comprises compensating for differencesbetween the biological reference signal and the artifact of thebiological reference signal.

Alternatively or additionally to the examples above, in another example,compensating for differences between the biological reference signal andthe artifact of the biological reference signal comprises generating oneor more shifted copies of the biological reference signal.

Alternatively or additionally to the examples above, in another example,compensating for differences between the biological reference signal andthe artifact of the biological reference signal comprises: generating,based at least in part on the generated one or more shifted copies ofthe biological reference signal, an estimated artifact of the biologicalreference signal.

Alternatively or additionally to the examples above, in another example,subtracting the artifact of the biological reference signal from thesensed biological source signal comprises subtracting the estimatedartifact of the biological reference signal from the sensed biologicalsource signal.

Alternatively or additionally to the examples above, in another example,generating, based at least in part on the generated one or more shiftedcopies of the biological reference signal, an estimated artifact of thebiological reference signal comprises: forming a projection matrixcomprising the biological reference signal and one or more shiftedcopies of the biological reference signal; determining a set of linearcombination coefficients using a projection technique; and forming theestimated artifact of the biological reference signal from theprojection matrix and the set of linear combination coefficients.

Alternatively or additionally to the examples above, in another example,the projection technique comprises one or more of: least-squaresregression; constrained least-squares; maximum likelihood estimation;non-linear programming; and linear programming.

Alternatively or additionally to the examples above, in another example,generating, based at least in part on the generated one or more shiftedcopies of the biological reference signal, an estimated artifact of thebiological reference signal comprises: generating a convolution matrix Hcomprising the biological reference signal and one or more shiftedcopies of the biological reference signal; and determining an optimalmultiplication vector x, such that a product of the convolution matrix Hand the optimal multiplication vector x produce a solution vector b′,where the solution vector b′ is a solution that is most closelycorrelated to the biological source signal.

Alternatively or additionally to the examples above, in another example,the method further comprises reducing redundancy in the biologicalreference signal.

Alternatively or additionally to the examples above, in another example,reducing the redundancy in the biological reference signal comprisesperforming principal component analysis on the biological referencesignal.

Alternatively or additionally to the examples above, in another example,the method further comprises identifying beat timings in the biologicalreference signal.

Alternatively or additionally to the examples above, in another example,the method further comprises: identifying beat windows around theidentified beat timings in the biological reference signal and thebiological source signal; and concatenating the beat windows to producea concatenated biological reference signal and a concatenated biologicalsource signal.

In still another example, a catheter system for mapping a chamber of aheart comprises: a plurality of electrodes configured to sense a firstset of one or more activation signals in the chamber of the heart,wherein each of the activation signals of the first set comprises anear-field signal component and a far-field signal component; one ormore electrodes configured to sense a second set of one or moreactivation signals, wherein the second set of activation signals arerepresentative of the far-field signal components of the first set ofactivation signals; and a processor configured to receive the sensedfirst set of one or more activation signals and the sensed second set ofone or more second activation signals, wherein the processor isconfigured to: process the second set of activation signals; generate,based at least in part on the processed second set of activationsignals, an estimated far-field signal component for each activationsignal in the first set of activation signals; and subtract theestimated far-field signal components from the corresponding firstactivation signals.

Alternatively or additionally to the examples above, in another example,to generate, based at least in part on the processed second set ofactivation signals, an estimated far-field signal component for eachactivation signal in the first set of activation signals, the processoris configured to: generate one or more shifted copies of the processedsecond set of activation signals; project the one or more shifted copiesonto each of the activation signals of first set of activation signals.

Alternatively or additionally to the examples above, in another example,projecting the one or more shifted copies onto each of the activationsignals of the first set of activation signals produces the estimatedfar-field signal component for each activation signal in the first setof activation signals, wherein the estimated far-field signal componentsare the estimated far-field signal components that are most closelycorrelated to the far-field signal components of the activation signalsin the first set of activation signals.

Alternatively or additionally to the examples above, in another example,projecting comprises performing one or more techniques comprised of:least-squares regression; constrained least-squares; maximum likelihoodestimation; non-linear programming; and linear programming.

Alternatively or additionally to the examples above, in another example,to process the second set of activation signals, the processor isconfigured to: produce one or more concatenated beat window signals fromthe one or more second activation signals.

In still another example, a method for reducing a ventricular signalartifact in a sensed atrial signal comprises: sensing one or moreventricular signals with a plurality of electrodes; sensing an atrialsignal using a plurality of electrodes, wherein the atrial signalcomprises an atrial signal component and an artifact signal componentthat is representative of the one or more ventricular signals; andfiltering, based at least in part on the sensed one or more ventricularsignals, the atrial signal to reduce the artifact signal component,wherein the filtering accounts for differences between the one or moreventricular signals and the artifact signal component.

Alternatively or additionally to the examples above, in another example,filtering, based at least in part on the sensed one or more ventricularsignals, the atrial signal to reduce the artifact signal component,comprises: generating one or more shifted copies of the one or moreventricular signals; generating, based at least in part on the generatedone or more shifted copies of the one or more ventricular signals, anestimated artifact signal; and subtracting the estimated artifact signalfrom the atrial signal.

Alternatively or additionally to the examples above, in another example,generating, based at least in part on the generated one or more shiftedcopies of the one or more ventricular signals, an estimated artifactsignal comprises back projecting the generated one or more shiftedcopies of the one or more ventricular signals onto the atrial signal.

The above summary of some embodiments is not intended to describe eachdisclosed embodiment or every implementation of the present disclosure.The Figures, and Detailed Description, which follow, more particularlyexemplify these embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may be more completely understood in consideration of thefollowing detailed description in connection with the accompanyingdrawings, in which:

FIG. 1 is a schematic view of an example catheter system for accessing atargeted tissue region in the body for diagnostic and therapeuticpurposes, in accordance with aspects of this disclosure;

FIG. 2 is a schematic view of an example mapping catheter having abasket functional element carrying structure for use in association withthe system of FIG. 1, in accordance with aspects of this disclosure;

FIG. 3 is a schematic view of an example functional element including aplurality of mapping electrodes, in accordance with aspects of thisdisclosure;

FIG. 4 is an illustration of sensed cardiac electrical signals, inaccordance with aspects of this disclosure;

FIG. 5 is an illustration of modified sensed cardiac electrical signals,in accordance with aspects of this disclosure;

FIG. 6A is another illustration of multiple cardiac electrical signals,in accordance with aspects of this disclosure;

FIG. 6B is another illustration of multiple cardiac electrical signals,in accordance with aspects of this disclosure

FIG. 7 is an illustration of a convolution matrix, in accordance withaspects of this disclosure;

FIG. 8 is an illustration of an example column vector, in accordancewith aspects of this disclosure;

FIG. 9 is another illustration of an example column vector, inaccordance with aspects of this disclosure;

FIG. 10 is an illustration of example beat windows, in accordance withaspects of this disclosure;

FIG. 11 is an illustrative technique in accordance with this disclosurethat may be performed by a catheter system, such as that depicted inFIG. 1; and

FIG. 12 is another illustrative technique in accordance with thisdisclosure that may be performed by a catheter system, such as thatdepicted in FIG. 1.

While the disclosure is amenable to various modifications andalternative forms, specifics thereof have been shown by way of examplein the drawings and will be described in detail. It should beunderstood, however, that the intention is not to limit the invention tothe particular embodiments described. On the contrary, the intention isto cover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the disclosure.

DETAILED DESCRIPTION

For the following defined terms, these definitions shall be applied,unless a different definition is given in the claims or elsewhere inthis specification.

All numeric values are herein assumed to be modified by the term“about,” whether or not explicitly indicated. The term “about” generallyrefers to a range of numbers that one of skill in the art would considerequivalent to the recited value (e.g., having the same function orresult). In many instances, the terms “about” may include numbers thatare rounded to the nearest significant figure.

The recitation of numerical ranges by endpoints includes all numberswithin that range (e.g. 1 to 5 includes 1, 1.5, 2, 2.75, 3, 3.80, 4, and5).

As used in this specification and the appended claims, the singularforms “a”, “an”, and “the” include plural referents unless the contentclearly dictates otherwise. As used in this specification and theappended claims, the term “or” is generally employed in its senseincluding “and/or” unless the content clearly dictates otherwise.

It is noted that references in the specification to “an example”, “someexamples”, “other examples”, etc., indicate that the example describedmay include one or more particular features, structures, and/orcharacteristics. However, such recitations do not necessarily mean thatall examples include the particular features, structures, and/orcharacteristics. Additionally, when particular features, structures,and/or characteristics are described in connection with one example, itshould be understood that such features, structures, and/orcharacteristics may also be used connection with other examples whetheror not explicitly described unless clearly stated to the contrary. Also,when particular features, structures, and/or characteristics aredescribed in connection with one example, it is implicit that otherexamples may include less than all of the disclosed features,structures, and/or characteristics in all combinations.

The following detailed description should be read with reference to thedrawings in which similar elements in different drawings are numberedthe same. The drawings, which are not necessarily to scale, depictillustrative embodiments and are not intended to limit the scope of theinvention.

Mapping the electrophysiology of heart rhythm disorders often involvesthe introduction of a constellation catheter or other mapping/sensingdevice having a plurality of electrodes and/or sensors (e.g.,CONSTELLATION®, commercially available from Boston Scientific) into acardiac chamber. The sensors, for example electrodes, detect cardiacelectrical activity at sensor locations. It may be desirable to have thecardiac electrical activity processed into electrogram signals thataccurately represent cellular excitation through cardiac tissue relativeto the sensor locations. A processing system may then analyze and outputthe signal to a display device. Further, the processing system mayoutput the signal as an activation or vector field map. A user, such asa physician, may use the activation or vector field map to perform adiagnostic procedure.

Some example catheters may include sixty-four or more electrodes whicheach detect cardiac electrical activity. Such electrodes may sensecardiac electrical activity that originates near the electrodes, e.g.near field signals, and cardiac electrical activity that originates awayfrom the electrodes, e.g. far-field signals. In some cases, theelectrodes may sense activity from both locations at similar times, suchthat the sensed signal is a combination of signals from each source.This disclosure describes various medical devices and techniques formodifying sensed electrical signals.

FIG. 1 is a schematic view of a system 10 for accessing a targetedtissue region in the body for diagnostic and/or therapeutic purposes.FIG. 1 generally shows the system 10 deployed in the left atrium of theheart. Alternatively, system 10 can be deployed in other regions of theheart, such as the left ventricle, right atrium, or right ventricle.While the illustrated embodiment shows system 10 being used for ablatingmyocardial tissue, system 10 (and the techniques described herein) mayalternatively be configured for use in other tissue ablationapplications, such as procedures for ablating tissue in the prostrate,brain, gall bladder, uterus, nerves, blood vessels and other regions ofthe body, including in systems that are not necessarily catheter-based.

System 10 includes mapping probe 14 and ablation probe 16. Each probe14/16 may be separately introduced into the selected heart region 12through a vein or artery (e.g., the femoral vein or artery) using asuitable percutaneous access technique. Alternatively, mapping probe 14and ablation probe 16 can be assembled in an integrated structure forsimultaneous introduction and deployment in the heart region 12.

Mapping probe 14 may include flexible catheter body 18. The distal endof catheter body 18 carries three-dimensional multiple electrodestructure 20. In the illustrated embodiment, structure 20 takes the formof a basket defining an open interior space 22 (see FIG. 2), althoughother multiple electrode structures could be used. Structure 20 carriesa plurality of mapping electrodes 24 (not explicitly shown on FIG. 1,but shown on FIG. 2) each having an electrode location on structure 20and a conductive member. Each electrode 24 may be configured to sense ordetect intrinsic physiological activity in an anatomical region adjacentto each electrode 24.

In some examples, electrodes 24 may be configured to detect activationsignals of the intrinsic physiological activity within the anatomicalstructure. For example, intrinsic cardiac electrical activity maycomprise repeating or semi-repeating waves of electrical activity withrelatively large spikes in activity at the beginning of activationevents. Electrodes 24 may sense such activation events and the times atwhich such activation events occur. Generally, electrodes 24 may senseactivation events at different times as an electrical activity wavepropagates through the heart. For instance, an electrical wave may beginnear a first group of electrodes 24, which may sense an activation eventat relatively the same time or within a relatively small window of time.As the electrical wave propagates through the heart, a second group ofelectrodes 24 may sense the activation even of the electrical wave attimes later than the first group of electrodes 24.

Electrodes 24 are electrically coupled to processing system 32. A signalwire (not shown) may be electrically coupled to each electrode 24 onstructure 20. The signal wires may extend through body 18 of probe 14and electrically couple each electrode 24 to an input of processingsystem 32. Electrodes 24 sense cardiac electrical activity in theanatomical region, e.g., myocardial tissue, adjacent to their physicallocation within the heart. The sensed cardiac electrical activity (e.g.,electrical signals generated by the heart which may include activationsignals) may be processed by processing system 32 to assist a user, forexample a physician, by generating an anatomical map (e.g., a vectorfield map, an activation time map) to identify one or more sites withinthe heart appropriate for a diagnostic and/or treatment procedure, suchas an ablation procedure. For example, processing system 32 may identifya near-field signal component (e.g., activation signals originating fromcellular tissue adjacent to mapping electrodes 24) or an obstructivefar-field signal component (e.g., activation signals originating fromnon-adjacent tissue). In such examples where structure 20 is disposed inan atrium of the heart, as in FIG. 1, the near-field signal componentmay include activation signals originating from atrial myocardial tissuewhereas the far-field signal component may include activation signalsoriginating from ventricular myocardial tissue. In some instances, auser may only be interested in the near-field signal component, andsystem 10 may be configured to process the sensed signals to remove thesensed far-field signal component. The near-field activation signalcomponent may then be further analyzed to find the presence of apathology and to determine a location suitable for ablation fortreatment of the pathology (e.g., ablation therapy).

Processing system 32 may include dedicated circuitry (e.g., discretelogic elements and one or more microcontrollers; application-specificintegrated circuits (ASICs); or specially configured programmabledevices, such as, for example, programmable logic devices (PLDs) orfield programmable gate arrays (FPGAs)) for receiving and/or processingthe acquired cardiac electrical activity. In some examples, processingsystem 32 includes a general purpose microprocessor and/or a specializedmicroprocessor (e.g., a digital signal processor, or DSP, which may beoptimized for processing activation signals) that executes instructionsto receive, analyze and display information associated with the receivedcardiac electrical activity. In such examples, processing system 32 caninclude program instructions, which when executed, perform part of thesignal processing. Program instructions can include, for example,firmware, microcode or application code that is executed bymicroprocessors or microcontrollers. The above-mentioned implementationsare merely exemplary, and the reader will appreciate that processingsystem 32 can take any suitable form for receiving electrical signalsand processing the received electrical signals.

In some examples, processing system 32 may be configured to measure thesensed cardiac electrical activity in the myocardial tissue adjacent toelectrodes 24. For example, processing system 32 may be configured todetect cardiac electrical activity associated with a dominant rotor ordivergent activation pattern in the anatomical feature being mapped.Dominant rotors and/or divergent activation patterns may have a role inthe initiation and maintenance of atrial fibrillation, and ablation ofthe rotor path, rotor core, and/or divergent foci may be effective interminating the atrial fibrillation. Processing system 32 processes thesensed cardiac electrical activity to generate a display of relevantcharacteristics, such as an isochronal map, activation time map, actionpotential duration (APD) map, a vector field map, a contour map, areliability map, an electrogram, a cardiac action potential and thelike. The relevant characteristics may assist a user to identify a sitesuitable for ablation therapy.

Ablation probe 16 includes flexible catheter body 34 that carries one ormore ablation electrodes 36. The one or more ablation electrodes 36 areelectrically connected to radio frequency (RF) generator 37 that isconfigured to deliver ablation energy to the one or more ablationelectrodes 36. Ablation probe 16 may be movable with respect to theanatomical feature to be treated, as well as structure 20. Ablationprobe 16 may be positionable between or adjacent to electrodes 24 ofstructure 20 as the one or more ablation electrodes 36 are positionedwith respect to the tissue to be treated.

Processing system 32 may output data to a suitable device, for exampledisplay device 40, which may display relevant information for a user. Insome examples, device 40 is a CRT, LED, or other type of display, or aprinter. Device 40 presents the relevant characteristics in a formatuseful to the user. In addition, processing system 32 may generateposition-identifying output for display on device 40 that aids the userin guiding ablation electrode(s) 36 into contact with tissue at the siteidentified for ablation.

FIG. 2 illustrates mapping catheter 14 and shows electrodes 24 at thedistal end suitable for use in system 10 shown in FIG. 1. Mappingcatheter 14 may include flexible catheter body 18, the distal end ofwhich may carry three-dimensional multiple electrode structure 20 withmapping electrodes or sensors 24. Mapping electrodes 24 may sensecardiac electrical activity, including activation signals, in themyocardial tissue. The sensed cardiac electrical activity may beprocessed by the processing system 32 to assist a user in identifyingthe site or sites having a heart rhythm disorder or other myocardialpathology via generated and displayed relevant characteristics. Thisinformation can then be used to determine an appropriate location forapplying appropriate therapy, such as ablation, to the identified sites,and to navigate the one or more ablation electrodes 36 to the identifiedsites.

The illustrated three-dimensional multiple electrode structure 20comprises base member 41 and end cap 42 between which flexible splines44 generally extend in a circumferentially spaced relationship. Asdiscussed herein, structure 20 may take the form of a basket defining anopen interior space 22. In some examples, the splines 44 are made of aresilient inert material, such as Nitinol, other metals, siliconerubber, suitable polymers, or the like and are connected between basemember 41 and end cap 42 in a resilient, pretensioned condition, to bendand conform to the tissue surface they contact. In the exampleillustrated in FIG. 2, eight splines 44 form three dimensional multipleelectrode structure 20. Additional or fewer splines 44 could be used inother examples. As illustrated, each spline 44 carries eight mappingelectrodes 24. Additional or fewer mapping electrodes 24 could bedisposed on each spline 44 in other examples of three dimensionalmultiple electrode structure 20. In the example illustrated in FIG. 2,structure 20 is relatively small (e.g., 40 mm or less in diameter). Inalternative examples, structure 20 is even smaller or larger (e.g., lessthan or greater than 40 mm in diameter).

Slidable sheath 50 may be movable along the major axis of catheter body18. Moving sheath 50 distally relative to catheter body 18 may causesheath 50 to move over structure 20, thereby collapsing structure 20into a compact, low profile condition suitable for introduction intoand/or removal from an interior space of an anatomical structure, suchas, for example, the heart. In contrast, moving sheath 50 proximallyrelative to the catheter body may expose structure 20, allowingstructure 20 to elastically expand and assume the pretensed positionillustrated in FIG. 2.

A signal wire (not shown) may be electrically coupled to each mappingelectrode 24. The signal wires may extend through body 18 of mappingcatheter 20 (or otherwise through and/or along body 18) into handle 54,in which they are coupled to external connector 56, which may be amultiple pin connector. Connector 56 electrically couples mappingelectrodes 24 to processing system 32. It should be understood thatthese descriptions are just examples. Some addition details regardingthese and other example mapping systems and methods for processingsignals generated by a mapping catheter can be found in U.S. Pat. Nos.6,070,094, 6,233,491, and 6,735,465, the disclosures of which are herebyexpressly incorporated herein by reference.

To illustrate the operation of system 10, FIG. 3 is a schematic sideview of an example of basket structure 20 including a plurality ofmapping electrodes 24. In the illustrated example, the basket structureincludes 64 mapping electrodes 24. Mapping electrodes 24 are disposed ingroups of eight electrodes (labeled 1, 2, 3, 4, 5, 6, 7, and 8) on eachof eight splines (labeled A, B, C, D, E, F, G, and H). While anarrangement of sixty-four mapping electrodes 24 is shown disposed onbasket structure 20, mapping electrodes 24 may alternatively be arrangedin different numbers (more or fewer splines and/or electrodes), ondifferent structures, and/or in different positions. In addition,multiple basket structures can be deployed in the same or differentanatomical structures to simultaneously obtain signals from differentanatomical structures.

After basket structure 20 is positioned adjacent to the anatomicalstructure to be treated (e.g. left atrium, left ventricle, right atrium,or right ventricle of the heart), processing system 32 is configured torecord the cardiac electrical activity from each electrode 24 channel,and the cardiac electrical activity is related to physiological activityof the adjacent anatomical structure. For instance, cardiac electricalactivity may include activation signals which may indicate an onset ofphysiological activity, such as a contraction of the heart. Electrodes24 sense such cardiac electrical activity which includes activationsignals. The cardiac electrical activity of physiological activity maybe sensed in response to intrinsic physiological activity (e.g.intrinsically generated electrical signals) or based on a predeterminedpacing protocol instituted by at least one of the plurality ofelectrodes 24 (e.g. delivered electrical signals delivered by a pacingdevice).

The arrangement, size, spacing and location of electrodes along aconstellation catheter or other mapping/sensing device, in combinationwith the specific geometry of the targeted anatomical structure, maycontribute to the ability (or inability) of electrodes 24 to sense,measure, collect and transmit electrical activity of cellular tissue. Asstated, because splines 44 of a mapping catheter, constellation catheteror other similar sensing device are bendable, they may conform to aspecific anatomical region in a variety of shapes and/or configurations.Further, at any given position in the anatomical region, structure 20may be manipulated such that one or more splines 44 may not contactadjacent cellular tissue. For example, splines 44 may twist, bend, orlie atop one another, thereby separating splines 44 from nearby cellulartissue. Additionally, because electrodes 24 are disposed on one or moreof splines 44, they also may not maintain contact with adjacent cellulartissue. Electrodes 24 that do not maintain contact with cellular tissuemay be incapable of sensing, detecting, measuring, collecting and/ortransmitting electrical activity information. Further, becauseelectrodes 24 may be incapable of sensing, detecting, measuring,collecting and/or transmitting electrical activity information,processing system 32 may be incapable of accurately displayingdiagnostic information. For example, some necessary information may bemissing and/or displayed inaccurately.

In addition to that stated above, electrodes 24 may not be in contactwith adjacent cellular tissue for other reasons. For example,manipulation of mapping catheter 14 may result in movement of electrodes24, thereby creating poor electrode-to-tissue contact. Further,electrodes 24 may be positioned adjacent fibrous, dead or functionallyrefractory tissue. Electrodes 24 positioned adjacent fibrous, dead orfunctionally refractory tissue may not be able to sense changes inelectrical potential because fibrous, dead or functionally refractorytissue may be incapable of depolarizing and/or responding to changes inelectrical potential. Finally, far-field ventricular events andelectrical line noise may distort measurement of tissue activity.

However, electrodes 24 that contact healthy, responsive cellular tissuemay sense cardiac electrical activity such as a change in the voltagepotential of a propagating cellular activation wavefront. Further, in anormal functioning heart, electrical discharge of the myocardial cellsmay occur in a systematic, linear fashion. Therefore, detection ofnon-linear propagation of the cellular excitation wavefront may beindicative of cellular firing in an abnormal fashion. For example,cellular firing in a rotating pattern may indicate the presence ofdominant rotors and/or divergent activation patterns. Further, becausethe presence of the abnormal cellular firing may occur over localizedtarget tissue regions, it is possible that electrical activity maychange form, strength or direction when propagating around, within,among or adjacent to diseased or abnormal cellular tissue.Identification of these localized areas of diseased or abnormal tissuemay provide a user with a location for which to perform a therapeuticand/or diagnostic procedure. For example, identification of an areaincluding reentrant or rotor currents may be indicative of an area ofdiseased or abnormal cellular tissue. The diseased or abnormal cellulartissue may be targeted for an ablative procedure. An activation time mapmay be used to identify areas of circular, adherent, rotor or otherabnormal cellular excitation wavefront propagation.

As discussed above, in some instances, it may be desirable to filter thesensed cardiac electrical activity, such as by removing far-fieldsignals from the signals sensed by electrodes 24. Generally, system 10may be configured to gather a source signal and a reference signal. Thesource signal, sensed for instance by electrodes 24, comprises both anear-field signal component and a far-field signal component. Thefar-field signal component may be a far-field signal artifact. Forinstance, the far-field signal may become distorted as the far-fieldsignal propagates from its source to electrodes 24. This distortedfar-field signal sensed by electrodes 24 is the far-field signalartifact present in the source signal. System 10 may additionally sensea reference signal, which may be a representation of the far-fieldsignal component. System 10 may further process the reference signal todetermine an estimation of the far-field signal artifact and subtractthe estimated far-field signal artifact from the source signal, therebyleaving only the near-field signal component of the source signal.

In some examples, the near-field signal component referenced herein maybe an atrial signal sensed by electrodes 24 disposed in an atrium of aheart. In such examples, the far-field artifacts may be ventricularsignals conducted through the tissue of the patient and received byelectrodes 24, along with the near-field signal component. In suchcases, it may be desirable to remove the sensed ventricular signals fromthe signals sensed by electrodes 24 to get a clearer picture of theatrial signals. However, the techniques described herein are morebroadly applicable than with respect to atrial signals and ventricularsignals. Accordingly, this disclosure may use the term near-field signalcomponent to describe a signal sensed by an electrode which is generatedadjacent to the electrode and far-field signal artifact to describe asignal that is generated remote from the electrode that is still sensedby the electrode.

In order to gather a reference signal, processing system 32 may furtherinclude external electrodes 15, as shown in FIG. 1. External electrodes15 may be electrodes external to mapping probe 14. In some examples,external electrodes 15 may be configured in a standard 12-lead surfaceEKG configuration. During times of atrial flutter or atrialfibrillation, the atrial signals generated by the atria may be erraticand unsynchronized. Accordingly, atrial signals reaching externalelectrodes 15 on the surface of the patient may tend to become minimizedrelative to ventricular signals because the erratic and unsynchronizedatrial signals may cancel each other, at least to some extent. In someexamples, external electrodes 15 may be configured in otherconfigurations, such as in the Frank configuration, with threeelectrodes configured in completely orthogonal directions.

In other examples, external electrodes 15 may be electrodes which areinternal to the patient's body. For instance, external electrodes 15 maybe electrodes disposed within a ventricle or other chamber of the heart.In still other examples, system 10 may not include external electrodes15. In such examples, electrodes 24 may sense the reference signal.Processing system 32 may additionally processes the reference signalssensed by electrodes 24, or external electrodes 15 disposed within otherchambers of the heart, by averaging multiple sensed signals in order tominimize the near-field atrial signals.

The above techniques for gathering a reference signal are only somepossible examples. Generally, the techniques disclosed herein may beperformed using any signal as a reference signal. However, using areference signal with a few particular qualities may help to increasethe accuracy of the described techniques. First, the reference signalmay comprise at least some data from three dimensions. Further, the morecomplete the data from each dimension, generally the higher the accuracyof the described techniques may tend to be. For example, such threedimensional data may be obtained by using a standard 12-leadconfiguration or the Frank lead configuration, as described previously.Additionally, the reference signal should be uncorrelated with respectto intrinsic atrial electrical activity. That is not to say that thereference signal needs to be completely uncorrelated with respect tointrinsic atrial electrical activity. Rather, the lower the correlationbetween the reference signal and the intrinsic atrial electricalactivity, generally the higher the accuracy of the described techniques.For example, as described above, signals sensed by surface electrodesduring atrial flutter or fibrillation may be sufficient sources oflow-correlation signals. However, in other examples, processing system32 may process other sensed signals to reduce atrial electrical activityin order to generate a reference signal.

After gathering a reference signal, either by sensing a signal withappropriate characteristics, or by processing a signal to generate asignal with appropriate characteristics, system 10 may then generate oneor more windows around detected beats, as shown in FIG. 4. For example,system 10 may use a peak detector and/or a QRS detector to determineR-waves and/or QRS complexes, for example QRS complexes 402 a, 402 b,and 402 c, present in reference signal 420. System 10 may then generatea beat window surrounding each detected R-wave and/or QRS complex. Thebeat window may extend a length 408 from a reference point to a pointprior to the reference point. The beat window may additionally extend alength 410 from a reference point to a point subsequent to the referencepoint. In some examples, the reference point may be a peak of theR-wave. In other examples, the reference point may be a point of maximumnegative slope of the QRS complex. In other examples, the referencepoint may be any other identifiable point within or near a detectedR-wave and/or QRS complex.

In some examples, the beat windows may have predetermined dimensions.For example length 408 may be one-hundred milliseconds, and length 410may be three-hundred milliseconds. However, in other examples, length408 may be fifty, two-hundred, or three-hundred milliseconds, or anyother suitable length of time. Similarly, in other examples, length 410may be fifty, one-hundred, or two-hundred milliseconds, or any othersuitable length of time. In some examples, lengths 408 and 410 may bedefined by a user, thereby allowing the beat window size to beadjustable. For instance, a user may enter input into display 40specifying values for length 408 and length 410.

After generating beat windows around the identified R-waves and/or QRScomplexes, system 10 may concatenate the beat windows, as shown in FIG.5. For example, system 10 may eliminate any data which does not fallwithin a beat window, thereby creating a new signal comprised of onlysignal data which fell within a beat window. The new signal may betermed the concatenated reference signal and is represented byconcatenated reference signal 430 in FIG. 5.

System 10 may additionally gather one or more source signals. Forinstance, system 10 may sense a signal with each of electrodes 24. Eachof these sensed signals may be a source signal. In some examples, system10 may gather the one or more source signals sensed by electrodes 24 atthe same time as gathering the reference signal. Accordingly, the datarepresented by the one or more source signals and the reference signalmay represent information about the same cardiac cycle or cycles. Afterdetermining one or more beat windows in the reference signal, system 10may determine beat windows in each of the one or more source signals attime ranges corresponding to those time ranges of the beat windowsformed in the reference signal. As with the reference signal, system 10may concatenate the determined beat windows in each of the one or moresource signals, thus forming one or more concatenated source signals.This ensures that the data in the one or more source signals istime-aligned with the data in the reference signal.

System 10 may proceed to perform one or more processing techniques onthe concatenated reference signal. For instance, system 10 may employone of a number of linear or non-linear dimensionality reductiontechniques on the concatenated reference signal. One lineardimensionality reduction technique that system 10 may employ isprincipal component analysis (PCA). However, in other examples, system10 may employ other known linear or non-linear dimensionality reductiontechniques to reduce the dimensionality of the concatenated referencesignal.

As described previously, the reference signal may be a representation ofthe far-field signal component of the source signal. The morphology ofthe reference signal may become distorted as it propagates from thetissue generating the reference signal through the body before beingsensed by electrodes 24 as a far-field artifact. Accordingly, thefar-field signal artifact present in the source signal may bemorphologically different than the sensed reference signal. For example,the body tissue may be modeled as an R-C network through which the heartsignal propagates before being sensed by electrodes 24. It is thepropagation through such an R-C network that imparts time and/or spatialdispersion on the reference signal as it propagates throughout the bodytissue. Accordingly, system 10 may apply an inverse system in order tocompensate for such morphological differences between the sensedreference signal and the far-field signal artifact present in the sourcesignal to generate an estimate of the far-field signal artifact presentin the source signal based on the sensed reference signal. System 10 maythen subtract out the estimated far-field signal artifact from thesource signal.

In some examples, system 10 may compensate for any dispersion of thereference signal by generating one or more shifted copies of thereference signal. For example, as depicted in FIG. 6A, system 10 maygenerate a copy of reference signal 420 that is shifted in time to theright, as evidenced by arrow 425, which may be termed shifted referencesignal 421. System 10 may further form beat windows in reference signal421 at the same (un-shifted) time ranges as in reference signal 420.FIG. 6A illustrates this concept as beat windows 404 a-c are the samebeat windows as depicted in FIGS. 4 and 5, which were formed around QRSwaves 402 a-c, as opposed to being formed based on features of shiftedreference signal 421. System 10 may further concatenate the beat windowsformed for shifted reference signal 421. This may result inshiftedconcatenated reference signal 432, as displayed in FIG. 6B. In otherexamples, system 10 may generate a copy of concatenated reference signal430 and then shift concatenated reference signal 430 in time to theright to generate a shifted concatenated reference signal instead ofgenerating a shifted copy of reference signal 420 and then concatenatingthe shifted reference signal.

System 10 may shift reference signal 420 or concatenated referencesignal 430 by simply shifting the individual samples of thecorresponding signal by some amount of samples, which may be termed ashift value. Some example shift values include five, eight, ten, eleven,fifteen, and twenty samples; however any number of samples may be usedin other examples. In some examples, the shift value may bepredetermined. In other examples, the shift value may be a user definedvalue. For instance, a user may enter a shift value into display 40.Processing system 32 may receive such a shift value and use the inputshift value for generating shifted copies of concatenated referencesignal 430.

In some examples, system 10 may generate a plurality of shiftedconcatenated reference signals 432, either by shifting reference signal420 and then concatenating the shifted signals or by shiftingconcatenated reference signal 430, as described above. To generate theplurality of shifted concatenated reference signals, system 10 may shiftthe reference signal 420 by a number of samples that are multiples ofthe first shift value. For example, if system 10 generates three shiftedcopies of concatenated reference signal 430, the first copy may beshifted by a shift value of eleven samples. The second copy may shiftedby twice the shift value, which is twenty-two samples. The third copymay be shifted by three-times the shift value, which is thirty-threesamples. In some examples, system 10 may generate copies that areshifted in the opposite direction of shifted concatenated referencesignal 432. For example, system 10 may use negative multiples of theshift value for generating such copies that are shifted earlier in time.

In some examples, system 10 may generate a predetermined number ofshifted concatenated reference signals 432. For instance, system 10 maygenerate five, ten, fifteen, or twenty shifted copies of concatenatedreference signal 430, with any number of the shifted copies beingshifted earlier or later than the concatenated reference signal. Inother examples, a user may specify how many shifted concatenatedreference signals 432 system 10 generates. For example, a user may enterinto display 40 a number of shifted copies for system 10 to generate.Additionally, a user may enter a number of shifted copies that areshifted earlier with respect to concatenated reference signal 430 (tothe left of concatenated reference signal 430 as depicted in FIG. 6) andlater with respect to concatenated reference signal 430. In suchexamples, system 10 may generate sequential shifted concatenatedreference signals 430 by incrementing the multiple of the shift value.For instance, if a user entered five shifted copies with two copiesshifted earlier and three copies shifted later than concatenatedreference signal 430, system 10 may generate a first shiftedconcatenated reference signal 432 using a multiple of the shift value ofnegative two. System 10 may then increment the multiple of the shiftvalue by one and generate another shifted concatenated reference signal432 using a multiple of the shift value of negative one. System 10 maycontinue this process until system 10 has generated an amount of shiftedconcatenated reference signal 432 equal to the number input by the user.When generating such shifted copies, system 10 may skip generating ashifted concatenated reference signal 432 if the multiple of the shiftvalue is zero.

Once system 10 has generated one or more shifted concatenated referencesignals 432, system 10 may then project back the concatenated referencesignal and, in some examples, each of the shifted copies of theconcatenated reference signal onto each of the one or more sourcesignals using an error minimization technique. This may result indetermining a signal which results in a minimization of the referencesignal artifact in the source signal. One technique system 10 may employfor this process is to form a projection matrix comprising theconcatenated reference signal and the one or more shifted copies of theconcatenated reference signal.

In at least some examples, the projection matrix may take the form of aconvolution matrix. FIG. 7 depicts example convolution matrix 700.Convolution matrix 700 may include a number of columns, with each columnrepresenting a signal or signal component. For example, column 706 a mayrepresent a first component of the concatenated reference signal. Eachsymbol 720 of each column may represent an individual sample of thesignal or signal component. Accordingly, the “b_(A1)” symbol of column706 a may represent the first sample of the concatenated referencesignal, the “b_(A2)” symbol of column 706 a may represent the secondsample of the concatenated reference signal, and so on. Column 706 b mayrepresent a second component of the concatenated reference signal.Accordingly, in the example of FIG. 7, the concatenated reference signalcomprises two components. However, in other examples, the concatenatedreference signal may comprise more or fewer components

Columns 708 a, 708 b through 710 a, 710 b may all represent componentsof shifted copies of the concatenated reference signal. For example,column 708 a may represent a first component of a first shifted copy ofthe concatenated reference signal. Column 708 b may represent a secondcomponent of the first shifted copy of the concatenated referencesignal. Columns 710 a and 710 b may represent first and secondcomponents of a second shifted copy of the concatenated referencesignal. Although only explicitly depicted in FIG. 7 as including twoshifted copies of the concatenated reference signal, it should beunderstood that convolution matrix 700 may include an arbitrary amountof shifted copies of the concatenated reference signal.

The concatenated source signal may also be formed into a matrix. Forexample, the concatenated source signal may be sampled and arranged intoa matrix such as matrix 800 as shown in FIG. 8. Each element 820 ofmatrix 800 is an individual sample of the concatenated source signal andthe samples may be aligned with elements 720 of matrix 700, for instancewith the first sample positioned at the top of matrix 800 and the lastsample placed at the bottom of matrix 800. In examples where theconcatenated source signal includes only a single component, matrix 800may be a single column matrix, termed a column vector (as in FIG. 8).

System 10 may additionally generate a column vector, such as columnvector 900 of FIG. 9, which includes linear combination coefficients,represented by elements 920, as will be described below. Vector 900 maybe arranged to have the same number of elements as convolution matrix700 has components (columns). For ease of reference below, matrix 700may be referred to as matrix H_(b), matrix 800 may be referred to asvector b, and vector 900 may be referred to as vector x. When matrixH_(b) and vector x are multiplied together, they may produce avector-matrix product called vector b′, as in equation (1) below.

H _(b) x=b′  (1).

Vector b′ may be of same the dimension as vector b, i.e. matrix 800.Generally speaking, vector b′ may be an estimate or projection of vectorb, and may sometimes be referenced as the estimate of the far-fieldsignal artifacts of the concatenated source signal.

System 10 may be configured to determine a set of linear combinationcoefficients for vector x (e.g. the elements of vectors x) that resultin an optimal vector b′. The process system 10 may use to find suchlinear combination coefficients may commonly be called “projection.”Some well-known techniques in the art used in such a process includemethods of least-squares regression, constrained least-squares,maximum-likelihood estimation, and linear programming. Depending on thespecific technique used, the “optimal” vector b′ may be different—e.g.considered optimal for different purposes or reasons. In at least thecase of least squares projection, the solution for x that results in anoptimal vector b′ results in a vector b′ that most closely correlates tovector b.

Relating the above discussed matrices and vectors back to the source andreference signals, vector b, as described above, is a representation ofthe concatenated source signal. The concatenated source signal, asmentioned previously, is comprised of a mixture of near field signalcomponents and far-field signal artifacts. Matrix H_(b) includes one ormore concatenated reference signals and shifted concatenated referencesignals, which may include components that are representative of thefar-field signal artifacts present in the concatenated source signal.Determining vector b′ from matrix H_(b), then, results in a signal(vector b′) which has components that are closely correlated with thefar-field artifacts of the concatenated source signal.

Once system 10 has found the set of linear combination coefficients(e.g. the components of vector x) that produce an optimal vector b′,system 10 may then determine a contiguously sampled signal that is anestimate of the far-field signal artifacts of the contiguously sampledsource signal. For instance, system 10 perform the above describedprojection with beat windowed signals—matrix H_(b) and vector b′ bothcontain representations of concatenated beat-windowed signals. Afterdetermining the linear combination coefficients for vector x, system 10may generate additional matrix H_(c), where the columns of matrix H_(c)represent the contiguously sampled (e.g. non-concatenated) referencesignal (or signal components) and the contiguously sampled shiftedreference signals (or signal components). In other words, matrix H_(b)and matrix H_(c) may be similar except that matrix H_(b) containsrepresentations of the concatenated beat-windowed reference and shiftedreference signals and matrix H_(c) contains representations of thecontiguously sampled reference and shifted reference signals. System 10may then multiply vector x, containing the determined linear combinationcoefficients, with matrix producing a contiguously sampled signal(vector c′) as shown in equation (2).

H _(c) x=c′  (2).

Vector c′ may be similar to vector b′, except that vector c′ representsa contiguously sampled signal. In equation (2), system 10 used thevector x previously found to optimize the correlation between vector b′and the biological source signal. Accordingly, vector c′ represents thecomponents of matrix H_(c) that most closely correlate with thebiological source signal. As with matrix H_(b), matrix H_(c) may includecomponents that are representative of the far-field signal artifactspresent in the original source signal (e.g. the contiguously sampledsource signal). Accordingly, vector c′ is comprised of components thatare closely correlated with the far-field signal artifacts of theoriginal source signal. Vector c′ may also be termed the estimate of thefar-field signal artifacts in the source signal.

System 10 may finally subtract vector c′ from the original source signalto obtain a signal that is representative of the near-field signalcomponents of the original source signal. That is, as vector c′ is anestimate of the far-field signal artifacts in the original sourcesignal, subtracting vector c′ from the original source signal may leaveonly the near-field signal components of the original source signal.This difference between vector c′ and the original source signal may betermed the residual signal.

Having produced a residual signal for a single source signal, system 10may perform a similar process for each of the source signals. Forinstance, as described above, system 10 may include sixty-fourelectrodes which gather sixty-four source signals. Additionally asdescribed above, system 10 may further employ these signals in otherapplications such as for determining areas of a heart to ablate.

As described previously, in some procedures, this near-field signalcomponent is the signal of interest in determining areas of the heart toablate. For example, system 10 may additionally determine one or moreactivation times for each signal sensed by electrodes 24 in order togenerate one or more visual maps depicting information about the heart.For example, system 10 may operate according to the techniques describedin “MEDICAL DEVICES FOR MAPPING CARDIAC TISSUE”, filed Mar. 11, 2014,with a provisional application No. 61/951,266, and is commonly owned.Removing the far-field signal components of the sensed source signalsmay allow systems to more accurately determine activation timings and/orgenerate the one or more maps.

In some situations, however, the reference signal may also includecomponents that are representative of the near field signal componentsof the source signal. In such situations, matrices H_(b) and H_(c) willtherefore also contain components which are representative of thenear-field signal components of the source signal. Any resulting vectorsc′ and residual signals, then, may not be so cleanly split between thefar-field signal artifacts and near-field signal components of thesource signal. The earlier discussed processing techniques describedsome methods of de-emphasizing the near-field signal components and/oremphasizing the representations of the far-field signal artifactspresent in the reference signal for generating matrices H_(b) and H_(c).For example, performing PCA on the reference signal is one way ofemphasizing the representations of the far-field signal artifacts and/orde-emphasizing the near-field signal components (being relative to thesource signal), present in the reference signal. Thus, performing PCAmay serve to enhance the correlation between the reference signal andthe far-field artifacts present in the source signal. System 10 mayemploy other techniques, however, to serve a similar end—either inaddition to or instead of such processing techniques.

For example, system 10, may determine multiple vector b's for a givensource signal. As described above, matrix H_(b) may comprise one or moreshifted concatenated reference signals, where each shifted concatenatedreference signal has been shifted by a number of samples equal to amultiple of a shift value. In some examples, system 10 may furthergenerate multiple matrices H_(b) by shifting the generated beat windows.For instance, as described above, when generating shifted referencesignals, system 10 kept the beat windows centered around the detectedQRS waves or peaks in the original reference signal. To generateadditional matrices H_(b), system 10 may use the generated shiftedreference signals, except move the beat windows within the shiftedreference signals as shown in FIG. 10. FIG. 10 shows shifted referencesignal 421 with beat windows 404 a-c. System 10 may shift beat windows404 a-c to the right, resulting in beat windows 406 a-c. By shifting thebeat windows in this way, system 10 is capturing slightly differentportions of the shifted reference signals for use in the additionalmatrices H_(b). In generating a first additional matrix H_(b), system 10may shift beat windows 404 a-c by a single sample. In generating asecond additional matrix H_(b), system 10 may shift beat windows 404 a-cby two samples. In some examples, system 10 may generate additionalmatrices in this manner equal to one less than the shift value.

System 10 may then perform a similar process to that described above forgenerating an optimal vector b′ for each of the generated additionalmatrices H_(b), thereby producing a number of vectors b′ for each sourcesignal. In such examples, system 10 may further determine correspondingerror vectors e, as shown in equation (3).

b=b′+e  (3).

Vector b, as described previously, represents the concatenated sourcesignal, and vector b′ represents the output of equation (1). Errorvector e, then, may represent the difference between vector b and vectorb′, and to the extent that vector b′ includes components that areclosely correlated to the far-field signal artifact present in theconcatenated source signal, error vector e may represent the near-fieldsignal component present in the concatenated source signal. Although, asmentioned previously, in some situations, vector b′ and vector e mayboth contain a mixture of near-field signal components andrepresentations of far-field signal components.

After generating a number of vectors b′ for each concatenated sourcesignal, system 10 may further create an average beat window for eachvector e by averaging the signals in each beat window for a given vectore. For example, as matrix H_(b) comprises signals made up ofconcatenated beat windows, the generated vectors b′, and thus vectors e,also are comprised of concatenated beat windows. Accordingly, system 10may then create an average beat window for each of the vectors e.Averaging the beat windows for each vector e may tend to minimize anynear-field signal component in vectors e and emphasize any presentfar-field signal artifacts. System 10 may then perform any of a numberof well-known error minimization techniques, such as RMS, mean absoluteerror, or the like, to determine which of vectors e is the leastcorrelated with its corresponding matrix H_(b)—thereby being the vectore with the least correlation to the far-field artifacts present in thesource signal and the vector e with the greatest correlation to the nearfield signal components of the source signal.

FIG. 11 is a flow diagram of an illustrative technique that may beimplemented by a catheter system such as shown in FIG. 1. Although themethod of FIG. 11 will be described with respect to the catheter systemof FIG. 1, the illustrative method of FIG. 11 may be performed by anysuitable catheter or medical device system.

In some examples, a catheter device, for instance catheter system 10,may include electrodes 24 which are disposed within a heart. System 10may be configured to sense a biological reference signal with electrodes24, as shown at 1102. System 10 may additionally be configured to sensea biological source signal, wherein the biological source signalcomprises an artifact of the biological reference signal, as shown at1104. System 10 may further be configured to determine, based on thebiological reference signal, the artifact of the biological referencesignal, as shown at 1106. For example, system 10 may generate one ormore shifted copies of the biological reference signal and back projectthe biological reference signal and the one or more shifted copies ofthe biological reference signal onto the biological source signal. Inother examples, system 10 may determine the artifact of the biologicalreference signal in other ways. Finally, system 10 may subtract theartifact of the biological reference signal from the sensed biologicalsource signal, as shown at 1108.

FIG. 12 is a flow diagram of an illustrative method that may beimplemented by a catheter system such as shown in FIG. 1. Although themethod of FIG. 12 will be described with respect to the catheter systemof FIG. 1, the illustrative method of FIG. 12 may be performed by anysuitable catheter system.

In some examples, a catheter device, for instance catheter system 10,may include electrodes 24 which are disposed within a heart. System 10may be configured to sense one or more ventricular signals with aplurality of electrodes, as shown at 1202. System 10 may further beconfigured to sense an atrial signal using a plurality of electrodes,wherein the atrial signal comprises an atrial signal component and anartifact signal component that is representative of the one or moreventricular signals, as shown at 1204. Finally, system 10 may beconfigured to filter, based at least in part on the sensed one or moreventricular signals, the atrial signal to reduce the artifact signalcomponent, wherein the filtering accounts for differences between theone or more ventricular signals and the artifact signal component, asshown at 1206.

The above described techniques represent only a few example techniquescontemplated by this disclosure. In other examples, system 10 mayprocess the source and reference signals to a lesser extent. Forexample, the techniques described herein may used without determiningbeat windows and producing concatenated signals. Instead, in suchexamples, system may perform PCA analysis on the unmodified referencesignal and perform the back projection with complete source signals anda complete reference. Additionally, in other examples, system 10 may notemploy PCA or any other dimensionality reduction technique before backprojecting. In some instances, such examples may produce results withsufficient accuracy that such additional steps are not necessary.

However, in other examples, system 10 may perform additional processingof the source and/or reference signals. For example, system 10 mayband-pass filter or otherwise perform well-known techniques in the artin order to reduce any noise interference present in the source and/orreference signals.

Additionally, although the above described techniques have beendescribed with respect to cardiac electrical signals, the process is notlimited in applicability to only cardiac electrical signals. Thetechniques described herein may be applicable to removing any far-fieldsignal artifacts that are morphologically different than the far-fieldsignal from a source signal including both a near-field signal componentof interest and an undesirable far-field artifact. For example, thetechniques described herein may be applicable to sensing electricalsignals generated by a brain of a patient and determining whichcomponents of a source signal are generated by a localized area of thebrain and which components of the source signal are due to far-fieldsignals conducted to the localized area.

What is claimed is:
 1. A system comprising: a plurality of electrodesconfigured to sense a biological source signal and a biologicalreference signal of a patient; and a processor configured to: receivethe biological source signal, wherein the biological source signalcomprises an artifact of the biological reference signal; determinemorphological differences between the biological reference signal andthe artifact of the biological reference signal; determine the artifactof the biological reference signal based on the determined morphologicaldifferences; and subtract the determined artifact from the sensedbiological source signal.
 2. The system of claim 1, wherein to determinemorphological differences between the biological reference signal andthe artifact of the biological reference signal, the processor isconfigured to: generate one or more shifted copies of the biologicalreference signal.
 3. The system of claim 2, wherein to determine theartifact of the biological reference signal based on the determinedmorphological differences, the processor is configured to: generate,based at least in part on the generated one or more shifted copies ofthe biological reference signal, an estimated artifact of the biologicalreference signal.
 4. The system of claim 3, wherein to generate, basedat least in part on the generated one or more shifted copies of thebiological reference signal, an estimated artifact of the biologicalreference signal, the processor is configured to: form a projectionmatrix comprising the biological reference signal and one or moreshifted copies of the biological reference signal; determine a set oflinear combination coefficients using a projection technique; and formthe estimated artifact of the biological reference signal from theprojection matrix and the set of linear combination coefficients.
 5. Thesystem of claim 4, wherein the projection technique comprises at leastone of: a least-squares regression, a constrained least-squaresregression, a maximum likelihood estimation, non-linear programming, andlinear programming.
 6. The system of claim 3, wherein to generate, basedat least in part on the generated one or more shifted copies of thebiological reference signal, an estimated artifact of the biologicalreference signal, the processor is configured to: generate a convolutionmatrix comprising the biological reference signal and one or moreshifted copies of the biological reference signal; and determine anoptimal multiplication vector x, such that a product of the convolutionmatrix and the optimal multiplication vector x produce a solution vectorb′, where the solution vector b′ is a solution that is most closelycorrelated to the biological source signal.
 7. The system of claim 1,wherein to determine morphological differences between the biologicalreference signal and the artifact of the biological reference signal,the processor is configured to: model the patient's tissue as an R-Cnetwork.
 8. The system of claim 1, wherein the processor is furtherconfigured to perform principal component analysis on the biologicalreference signal to reduce redundancy in the biological referencesignal.
 9. The system of claim 1, wherein the processor is furtherconfigured to: identify beat windows around the identified beat timingsin the biological reference signal and the biological source signal; andconcatenate the beat windows to produce a concatenated biologicalreference signal and a concatenated biological source signal.
 10. Thesystem of claim 1, wherein to determine morphological differencesbetween the biological reference signal and the artifact of thebiological reference signal, the processor is configured to determinemorphological differences between the concatenated biological referencesignal and the artifact of the concatenated biological source signal;wherein to determine the artifact of the biological reference signalbased on the determined morphological differences, the processor isconfigured to determine the artifact of the concatenated biologicalreference signal based on the determined morphological differences; andwherein to subtract the determined artifact from the sensed biologicalsource signal, the processor is configured to subtract the determinedartifact from the concatenated sensed biological source signal.
 11. Amethod comprising: receiving a biological reference signal of a patient;and receiving a sensed biological source signal of the patient, whereinthe received biological source signal comprises an artifact of thereceived biological reference signal; determining a distortion of thereceived biological reference signal based on a location in which thereceived biological source signal was sensed; determining the artifactof the biological reference signal based on the determined distortion;and subtracting the determined artifact from the received biologicalsource signal.
 12. The method of claim 11, wherein determining adistortion of the received biological reference signal based on alocation in which the received biological source signal was sensedcomprises: generating one or more shifted copies of the receivedbiological reference signal.
 13. The method of claim 12, whereingenerating one or more shifted copies of the received biologicalreference signal comprises estimating, based at least in part on thegenerated one or more shifted copies of the biological reference signal,an artifact of the biological reference signal.
 14. The method of claim13, wherein estimating, based at least in part on the generated one ormore shifted copies of the biological reference signal, an artifact ofthe biological reference signal comprises: forming a projection matrixcomprising the biological reference signal and one or more shiftedcopies of the biological reference signal; determining a set of linearcombination coefficients using a projection technique; and forming theestimated artifact of the biological reference signal from theprojection matrix and the set of linear combination coefficients. 15.The method of claim 14, wherein the projection technique comprises atleast one of: a least-squares regression, a constrained least-squaresregression, a maximum likelihood estimation, non-linear programming, andlinear programming.
 16. The method of claim 13, wherein estimating,based at least in part on the generated one or more shifted copies ofthe biological reference signal, an artifact of the biological referencesignal comprises: generating a convolution matrix comprising thebiological reference signal and one or more shifted copies of thebiological reference signal; and determining an optimal multiplicationvector x, such that a product of the convolution matrix and the optimalmultiplication vector x produce a solution vector b′, where the solutionvector b′ is a solution that is most closely correlated to thebiological source signal.
 17. The method of claim 11, determining adistortion of the received biological reference signal based on alocation in which the received biological source signal was sensedcomprises modelling the patient's tissue as an R-C network.
 18. Themethod of claim 11, further comprising performing principal componentanalysis on the biological reference signal to reduce redundancy in thebiological reference signal.
 19. The method of claim 18, furthercomprising: identifying beat windows around the identified beat timingsin the biological reference signal and the biological source signal; andconcatenating the beat windows to produce a concatenated biologicalreference signal and a concatenated biological source signal.
 20. Themethod of claim 19, wherein determining a distortion of the receivedbiological reference signal comprises determining a distortion of theconcatenated biological reference signal; wherein determining theartifact of the biological reference signal based on the determineddistortion comprises determining the artifact of the concatenatedbiological reference signal based on the determined distortion; andwherein subtracting the determined artifact from the received biologicalsource signal comprises subtracting the determined artifact from theconcatenated biological source signal.